Exploring social representations of adapting to climate change using topic modeling and Bayesian networks

When something unfamiliar emerges or when something familiar does something unexpected people need to make sense of what is emerging or going on in order to act. Social representations theory suggests how individuals and society make sense of the unfamiliar and hence how the resultant social representations (SRs) cognitively, emotionally, and actively orient people and enable communication. SRs are social constructions that emerge through individual and collective engagement with media and with everyday conversations among people. Recent developments in text analysis techniques, and in particular topic modeling, provide a potentially powerful analytical method to examine the structure and content of SRs using large samples of narrative or text. In this paper I describe the methods and results of applying topic modeling to 660 micronarratives collected from Australian academics / researchers, government employees, and members of the public in 2010-2011. The narrative fragments focused on adaptation to climate change (CC) and hence provide an example of Australian society making sense of an emerging and conflict ridden phenomena. The results of the topic modeling reflect elements of SRs of adaptation to CC that are consistent with findings in the literature as well as being reasonably robust predictors of classes of action in response to CC. Bayesian Network (BN) modeling was used to identify relationships among the topics (SR elements) and in particular to identify relationships among topics, sentiment, and action. Finally the resulting model and topic modeling results are used to highlight differences in the salience of SR elements among social groups. The approach of linking topic modeling and BN modeling offers a new and encouraging approach to analysis for ongoing research on SRs.

Optimization of aqueous extraction conditions for the recovery of phenolic compounds and antioxidants from lemon pomace

The aim of this study was to optimize the aqueous extraction conditions for the recovery of phenolic compounds and antioxidant capacity of lemon pomace using response surface methodology. An experiment based on Box–Behnken design was conducted to analyse the effects of temperature, time and sample-to-water ratio on the extraction of total phenolic compounds, total flavonoids, proanthocyanidins and antioxidant capacity. Sample-to-solvent ratio had a negative effect on all the dependent variables, while extraction temperature and time had a positive effect only on TPC yields and ABTS antioxidant capacity. The optimal extraction conditions were 95 oC, 15 min, and a sample-to-solvent ratio of 1:100 g/ml. Under these conditions, the aqueous extracts had the same content of TPC and TF as well as antioxidant capacity in comparison with those of methanol extracts obtained by sonication. Therefore these conditions could be applied for further extraction and isolation of phenolic compounds from lemon pomace.

Measuring, Modeling, and Forecasting Volatility and Correlations from High-Frequency Data

This dissertation contains four essays that all share a common purpose: developing new methodologies to exploit the potential of high-frequency data for the measurement, modeling and forecasting of financial assets volatility and correlations. The first two chapters provide useful tools for univariate applications while the last two chapters develop multivariate methodologies. In chapter 1, we introduce a new class of univariate volatility models named FloGARCH models. FloGARCH models provide a parsimonious joint model for low frequency returns and realized measures, and are sufficiently flexible to capture long memory as well as asymmetries related to leverage effects. We analyze the performances of the models in a realistic numerical study and on the basis of a data set composed of 65 equities. Using more than 10 years of high-frequency transactions, we document significant statistical gains related to the FloGARCH models in terms of in-sample fit, out-of-sample fit and forecasting accuracy compared to classical and Realized GARCH models. In chapter 2, using 12 years of high-frequency transactions for 55 U.S. stocks, we argue that combining low-frequency exogenous economic indicators with high-frequency financial data improves the ability of conditionally heteroskedastic models to forecast the volatility of returns, their full multi-step ahead conditional distribution and the multi-period Value-at-Risk. Using a refined version of the Realized LGARCH model allowing for time-varying intercept and implemented with realized kernels, we document that nominal corporate profits and term spreads have strong long-run predictive ability and generate accurate risk measures forecasts over long-horizon. The results are based on several loss functions and tests, including the Model Confidence Set. Chapter 3 is a joint work with David Veredas. We study the class of disentangled realized estimators for the integrated covariance matrix of Brownian semimartingales with finite activity jumps. These estimators separate correlations and volatilities. We analyze different combinations of quantile- and median-based realized volatilities, and four estimators of realized correlations with three synchronization schemes. Their finite sample properties are studied under four data generating processes, in presence, or not, of microstructure noise, and under synchronous and asynchronous trading. The main finding is that the pre-averaged version of disentangled estimators based on Gaussian ranks (for the correlations) and median deviations (for the volatilities) provide a precise, computationally efficient, and easy alternative to measure integrated covariances on the basis of noisy and asynchronous prices. Along these lines, a minimum variance portfolio application shows the superiority of this disentangled realized estimator in terms of numerous performance metrics. Chapter 4 is co-authored with Niels S. Hansen, Asger Lunde and Kasper V. Olesen, all affiliated with CREATES at Aarhus University. We propose to use the Realized Beta GARCH model to exploit the potential of high-frequency data in commodity markets. The model produces high quality forecasts of pairwise correlations between commodities which can be used to construct a composite covariance matrix. We evaluate the quality of this matrix in a portfolio context and compare it to models used in the industry. We demonstrate significant economic gains in a realistic setting including short selling constraints and transaction costs.

Facilitators of recovery for step-up and step-down clients of a sub-acute residential mental health service

Exergetic, energetic, economic and environmental evaluation of concentrated solar power plants in Libya

The PhD project addresses the potential of using concentrating solar power (CSP) plants as a viable alternative energy producing system in Libya. Exergetic, energetic, economic and environmental analyses are carried out for a particular type of CSP plants. The study, although it aims a particular type of CSP plant – 50 MW parabolic trough-CSP plant, it is sufficiently general to be applied to other configurations. The novelty of the study, in addition to modeling and analyzing the selected configuration, lies in the use of a state-of-the-art exergetic analysis combined with the Life Cycle Assessment (LCA). The modeling and simulation of the plant is carried out in chapter three and they are conducted into two parts, namely: power cycle and solar field. The computer model developed for the analysis of the plant is based on algebraic equations describing the power cycle and the solar field. The model was solved using the Engineering Equation Solver (EES) software; and is designed to define the properties at each state point of the plant and then, sequentially, to determine energy, efficiency and irreversibility for each component. The developed model has the potential of using in the preliminary design of CSPs and, in particular, for the configuration of the solar field based on existing commercial plants. Moreover, it has the ability of analyzing the energetic, economic and environmental feasibility of using CSPs in different regions of the world, which is illustrated for the Libyan region in this study. The overall feasibility scenario is completed through an hourly analysis on an annual basis in chapter Four. This analysis allows the comparison of different systems and, eventually, a particular selection, and it includes both the economic and energetic components using the “greenius” software. The analysis also examined the impact of project financing and incentives on the cost of energy. The main technological finding of this analysis is higher performance and lower levelized cost of electricity (LCE) for Libya as compared to Southern Europe (Spain). Therefore, Libya has the potential of becoming attractive for the establishment of CSPs in its territory and, in this way, to facilitate the target of several European initiatives that aim to import electricity generated by renewable sources from North African and Middle East countries. The analysis is presented a brief review of the current cost of energy and the potential of reducing the cost from parabolic trough- CSP plant. Exergetic and environmental life cycle assessment analyses are conducted for the selected plant in chapter Five; the objectives are 1) to assess the environmental impact and cost, in terms of exergy of the life cycle of the plant; 2) to find out the points of weakness in terms of irreversibility of the process; and 3) to verify whether solar power plants can reduce environmental impact and the cost of electricity generation by comparing them with fossil fuel plants, in particular, Natural Gas Combined Cycle (NGCC) plant and oil thermal power plant. The analysis also targets a thermoeconomic analysis using the specific exergy costing (SPECO) method to evaluate the level of the cost caused by exergy destruction. The main technological findings are that the most important contribution impact lies with the solar field, which reports a value of 79%; and the materials with the vi highest impact are: steel (47%), molten salt (25%) and synthetic oil (21%). The “Human Health” damage category presents the highest impact (69%) followed by the “Resource” damage category (24%). In addition, the highest exergy demand is linked to the steel (47%); and there is a considerable exergetic demand related to the molten salt and synthetic oil with values of 25% and 19%, respectively. Finally, in the comparison with fossil fuel power plants (NGCC and Oil), the CSP plant presents the lowest environmental impact, while the worst environmental performance is reported to the oil power plant followed by NGCC plant. The solar field presents the largest value of cost rate, where the boiler is a component with the highest cost rate among the power cycle components. The thermal storage allows the CSP plants to overcome solar irradiation transients, to respond to electricity demand independent of weather conditions, and to extend electricity production beyond the availability of daylight. Numerical analysis of the thermal transient response of a thermocline storage tank is carried out for the charging phase. The system of equations describing the numerical model is solved by using time-implicit and space-backward finite differences and which encoded within the Matlab environment. The analysis presented the following findings: the predictions agree well with the experiments for the time evolution of the thermocline region, particularly for the regions away from the top-inlet. The deviations observed in the near-region of the inlet are most likely due to the high-level of turbulence in this region due to the localized level of mixing resulting; a simple analytical model to take into consideration this increased turbulence level was developed and it leads to some improvement of the predictions; this approach requires practically no additional computational effort and it relates the effective thermal diffusivity to the mean effective velocity of the fluid at each particular height of the system. Altogether the study indicates that the selected parabolic trough-CSP plant has the edge over alternative competing technologies for locations where DNI is high and where land usage is not an issue, such as the shoreline of Libya.

Thermodynamic modeling and microcalorimetry of nanostructured materials for capacitive thermal management of electronics

Transient power dissipation profiles in handheld electronic devices alternate between high and low power states depending on usage. Capacitive thermal management based on phase change materials potentially offers a fan-less thermal management for such transient profiles. However, such capacitive management becomes feasible only if there is a significant enhancement in the enthalpy change per unit volume of the phase change material since existing bulk materials such as paraffin fall short of requirements. In this thesis I propose novel nanostructured thin-film materials that can potentially exhibit significantly enhanced volumetric enthalpy change. Using fundamental thermodynamics of phase transition, calculations regarding the enhancement resulting from superheating in such thin film systems is conducted. Furthermore design of a microfabricated calorimeter to measure such enhancements is explained in detail. This work advances the state-of-art of phase change materials for capacitive cooling of handheld devices.

Purificação, modelagem e simulação da adsorção de bioprodutos por troca iônica em coluna de leito expandido

A produção de proteínas através de microrganismos tornou-se uma técnica muito importante na obtenção de compostos de interesse da indústria farmacêutica e alimentícia. Extratos brutos nos quais as proteínas são obtidas são geralmente complexos, contendo sólidos e células em suspensão. Usualmente, para uso industrial destes compostos, é necessário obtê-los puros, para garantir a sua atuação sem interferência. Um método que vem recebendo destaque especialmente nos últimos 10 anos é o uso da cromatografia de troca iônica em leito expandido, que combina em uma única etapa os passos de clarificação, concentração e purificação da molécula alvo, reduzindo assim o tempo de operação e também os custos com equipamentos para realização de cada etapa em separado. Combinado a este fato, a última década também é marcada por trabalhos que tratam da modelagem matemática do processo de adsorção de proteínas em resinas. Está técnica, além de fornecer informações importantes sobre o processo de adsorção, também é de grande valia na otimização da etapa de adsorção, uma vez que permite que simulações sejam feitas, sem a necessidade de gasto de tempo e material com experimentos em bancada, especialmente se é desejado uma ampliação de escala. Dessa forma, o objetivo desta tese foi realizar a modelagem e simulação do processo de adsorção de bioprodutos em um caldo bruto na presença de células, usando inulinase e C-ficocianina como objeto de estudo e purificar C-ficocianina utilizando resina de troca iônica em leito expandido. A presente tese foi então dividida em quatro artigos. O primeiro artigo teve como objeto de estudo a enzima inulinase, e a otimização da etapa de adsorção desta enzima em resina de troca iônica Streamline SP, em leito expandido, foi feita através da modelagem matemática e simulação das curvas de ruptura em três diferentes graus de expansão (GE). As máximas eficiências foram observadas quando utilizadas maiores concentrações de inulinase (120 a 170 U/mL), e altura de leito entre 20 e 30 cm. O grau de expansão de 3,0 vezes foi considerado o melhor, uma vez que a produtividade foi consideravelmente superior. O segundo artigo apresenta o estudo das condições de adsorção de C-ficocianina em resina de troca iônica, onde foi verificado o efeito do pH e temperatura na adsorção e após construída a isoterma de adsorção. A isoterma de adsorção da C-ficocianina em resina Streamline Q XL feita em pH 7,5 e a 25°C (ambiente), apresentou um bom ajuste ao modelo de Langmuir (R=0,98) e os valores qm (capacidade máxima de adsorção) e Kd (constante de equilíbrio) estimados pela equação linearizada da isoterma, foram de 26,7 mg/mL e 0,067mg/mL. O terceiro artigo aborda a modelagem do processo de adsorção de extrato não clarificado de C-ficocianina em resina de troca iônica Streamline Q XL em coluna de leito expandido. Três curvas de ruptura foram feitas em diferentes graus de expansão (2,0, 2,5 e 3,0). A condição de adsorção de extrato bruto não clarificado de C-ficocianina que se mostrou mais vantajosa, por apresentar maior capacidade de adsorção, é quando se alimenta o extrato até atingir 10% de saturação da resina, em grau de expansão 2,0, com uma altura inicial de leito de 30 cm. O último artigo originado nesta tese foi sobre a purificação de C-ficocianina através da cromatografia de troca iônica em leito expandido. Uma vez que a adsorção já havia sido estudada no artigo 2, o artigo 4 enfoca na otimização das condições de eluição, visando obter um produto com máxima pureza e recuperação. A pureza é dada pela razão entre a absorbância a 620 nm pela absorbância a 280 nm, e dizse que quando C-ficocianina apresenta pureza superior a 0,7 ela pode ser usada em como corante em alimentos. A avaliação das curvas de contorno indicou que a faixa de trabalho deve ser em pH ao redor de 6,5 e volumes de eluição próximos a 150 mL. Tais condições combinadas a uma etapa de pré-eluição com 0,1M de NaCl, permitiu obter C-ficocianina com pureza de 2,9, concentração 3 mg/mL, e recuperação ao redor de 70%.

DESIGN, MODELING, AND FABRICATION OF MICROROBOT LEGS

This dissertation presents work done in the design, modeling, and fabrication of magnetically actuated microrobot legs. Novel fabrication processes for manufacturing multi-material compliant mechanisms have been used to fabricate effective legged robots at both the meso and micro scales, where the meso scale refers to the transition between macro and micro scales. This work discusses the development of a novel mesoscale manufacturing process, Laser Cut Elastomer Refill (LaCER), for prototyping millimeter-scale multi-material compliant mechanisms with elastomer hinges. Additionally discussed is an extension of previous work on the development of a microscale manufacturing process for fabricating micrometer-sale multi-material compliant mechanisms with elastomer hinges, with the added contribution of a method for incorporating magnetic materials for mechanism actuation using externally applied fields. As both of the fabrication processes outlined make significant use of highly compliant elastomer hinges, a fast, accurate modeling method for these hinges was desired for mechanism characterization and design. An analytical model was developed for this purpose, making use of the pseudo rigid-body (PRB) model and extending its utility to hinges with significant stretch component, such as those fabricated from elastomer materials. This model includes 3 springs with stiffnesses relating to material stiffness and hinge geometry, with additional correction factors for aspects particular to common multi-material hinge geometry. This model has been verified against a finite element analysis model (FEA), which in turn was matched to experimental data on mesoscale hinges manufactured using LaCER. These modeling methods have additionally been verified against experimental data from microscale hinges manufactured using the Si/elastomer/magnetics MEMS process. The development of several mechanisms is also discussed: including a mesoscale LaCER-fabricated hexapedal millirobot capable of walking at 2.4 body lengths per second; prototyped mesoscale LaCER-fabricated underactuated legs with asymmetrical features for improved performance; 1 centimeter cubed LaCER-fabricated magnetically-actuated hexapods which use the best-performing underactuated leg design to locomote at up to 10.6 body lengths per second; five microfabricated magnetically actuated single-hinge mechanisms; a 14-hinge, 11-link microfabricated gripper mechanism; a microfabricated robot leg mechansim demonstrated clearing a step height of 100 micrometers; and a 4 mm x 4 mm x 5 mm, 25 mg microfabricated magnetically-actuated hexapod, demonstrated walking at up to 2.25 body lengths per second.

Simulação de um sistema de tratamento de águas residuais de lamas ativadas

A modelação matemática de Estações de Tratamento de Águas Residuais (ETAR) tem sido uma ferramenta de enorme utilidade nas fases de projeto e de exploração destas estruturas de tratamento. O presente estudo teve por objetivo principal construir um modelo matemático da ETAR de Bragança, em particular do seu tratamento biológico de lamas ativadas, com vista a avaliar, compreender e otimizar o seu desempenho. A construção do modelo foi efetuada com recurso ao ambiente de simulação WRc STOAT 5.0. O processo de lamas ativadas foi descrito pelo modelo de referência ASAL3. O modelo construído foi calibrado e validado com base em dados experimentais de 2015, obtidos no âmbito do programa de controlo analítico da ETAR. O modelo foi ainda utilizado para avaliar a qualidade do efluente em resposta a alterações do caudal e composição do afluente, a alterações de condições operacionais e a outras alternativas de tratamento. O modelo mostrou-se bastante adequado na descrição da evolução mensal da qualidade do efluente final da ETAR relativamente aos parâmetros Sólidos Suspensos Totais (SST) e Carência Bioquímica de Oxigénio (CBO5), embora apresente uma tendência para os subestimar em 1,5 e 3,5 mg/L, respetivamente. Em relação ao azoto total, os valores simulados aproximaram-se dos valores reais, quando se aumentaram as taxas de recirculação interna para 400%, um fator de cerca de 4 vezes superior. Os resultados do modelo e dos cenários mostram e reforçam o bom desempenho e a operação otimizada da ETAR em relação a remoção de SST e CBO5. Em relação ao azoto total, a ETAR não assegura de forma sistemática uma eficiência elevada, mas apresenta um bom desempenho, face ao que o modelo consegue explicar para as mesmas condições operacionais. Através do estudo de cenários procurou-se encontrar alternativas de tratamento eficientes e viáveis de remoção de azoto total, mas não se identificaram soluções que assegurassem decargas de azoto abaixo dos limites legais. Os melhores resultados que se alcançaram para a remoção deste contaminante estão associados ao aumento das taxas de recirculação interna do sistema pré-anóxico existente e a uma configuração do tipo Bardenpho de quatro estágios com alimentação distribuída, em proporções iguais, pelos dois estágios anóxicos. Outras soluções que envolvam tecnologias distintas podem e devem ser equacionadas em projetos futuros que visem a melhoria de eficiência de remoção de azoto da ETAR.

Transfer function-noise modeling and spatial interpolation to evaluate the risk of extreme (shallow) water-table levels in the Brazilian Cerrados

Water regimes in the Brazilian Cerrados are sensitive to climatological disturbances and human intervention. The risk that critical water-table levels are exceeded over long periods of time can be estimated by applying stochastic methods in modeling the dynamic relationship between water levels and driving forces such as precipitation and evapotranspiration. In this study, a transfer function-noise model, the so called PIRFICT-model, is applied to estimate the dynamic relationship between water-table depth and precipitation surplus/deficit in a watershed with a groundwater monitoring scheme in the Brazilian Cerrados. Critical limits were defined for a period in the Cerrados agricultural calendar, the end of the rainy season, when extremely shallow levels (< 0.5-m depth) can pose a risk to plant health and machinery before harvesting. By simulating time-series models, the risk of exceeding critical thresholds during a continuous period of time (e.g. 10 days) is described by probability levels. These simulated probabilities were interpolated spatially using universal kriging, incorporating information related to the drainage basin from a digital elevation model. The resulting map reduced model uncertainty. Three areas were defined as presenting potential risk at the end of the rainy season. These areas deserve attention with respect to water-management and land-use planning.

Software engineering: methods, modeling and teaching

Since the emergence of software engineering in the late 1960's as a response to the software crisis, researchers throughout the world are trying to give theoretical support to this discipline. Several points of view have to be reviewed in order to complete this task. In the middle 70's Frederick Brooks Jr. coined the term "silver bullet" suggesting the solution to several problems rela-ted to software engineering and, hence, we adopted such a metaphor as a symbol for this book. Methods, modeling, and teaching are the insights reviewed in this book. Some work related to these topies is presented by software engineering researchers, led by Ivar Jacobson, one of the most remarkable researchers in this area. We hope our work will contribute to advance in giving the theoretieal support that software engineering needs.

Healthcare Network Modeling and Analysis

Part 20: Health and Care Networks

Modeling and Mapping Agroforestry Aboveground Biomass in the Brazilian Amazon Using Airborne Lidar Data.

Agroforestry has large potential for carbon (C) sequestration while providing many economical, social, and ecological benefits via its diversified products. Airborne lidar is considered as the most accurate technology for mapping aboveground biomass (AGB) over landscape levels. However, little research in the past has been done to study AGB of agroforestry systems using airborne lidar data. Focusing on an agroforestry system in the Brazilian Amazon, this study first predicted plot-level AGB using fixed-effects regression models that assumed the regression coefficients to be constants. The model prediction errors were then analyzed from the perspectives of tree DBH (diameter at breast height)?height relationships and plot-level wood density, which suggested the need for stratifying agroforestry fields to improve plot-level AGB modeling. We separated teak plantations from other agroforestry types and predicted AGB using mixed-effects models that can incorporate the variation of AGB-height relationship across agroforestry types. We found that, at the plot scale, mixed-effects models led to better model prediction performance (based on leave-one-out cross-validation) than the fixed-effects models, with the coefficient of determination (R2) increasing from 0.38 to 0.64. At the landscape level, the difference between AGB densities from the two types of models was ~10% on average and up to ~30% at the pixel level. This study suggested the importance of stratification based on tree AGB allometry and the utility of mixed-effects models in modeling and mapping AGB of agroforestry systems.

Modeling and analysis of thermoelectric energy conversion efficiency in nanostructures.

116 p.

3D Block Modeling and Reserve Estimation of a Garnet Deposit

The purpose of this project is to develop a three-dimensional block model for a garnet deposit in the Alder Gulch, Madison County, Montana. Garnets occur in pre-Cambrian metamorphic Red Wash gneiss and similar rocks in the vicinity. This project seeks to model the percentage of garnet in a deposit called the Section 25 deposit using the Surpac software. Data available for this work are drillhole, trench and grab sample data obtained from previous exploration of the deposit. The creation of the block model involves validating the data, creating composites of assayed garnet percentages and conducting basic statistics on composites using Surpac statistical tools. Variogram analysis will be conducted on composites to quantify the continuity of the garnet mineralization. A three-dimensional block model will be created and filled with estimates of garnet percentage using different methods of reserve estimation and the results compared.